Determination of a physically-varying anatomical structure

ABSTRACT

The present invention relates to a data processing method for providing variation data which describe a physically-varying anatomical structure, in particular an indiscernible anatomical structure, in particular a non-enhancing tumour, comprising the steps of: providing second image data which describe a second image of a region of an anatomical body, wherein the region includes a second anatomical part which includes the physically-varying anatomical structure; providing first image data which represent a first image of the same region, wherein said same region includes a first anatomical part which does not include the physically-varying anatomical structure or which includes the physically-varying anatomical structure in a different physical state than in the second anatomical part; providing position change data which describe positional changes of corresponding image elements between the first image and the second image, on the basis of the first and second image data; and providing the variation data on the basis of the position change data.

The present invention relates to the determination of aphysically-varying anatomical structure, in particular an indiscernibleanatomical structure, in particular a non-enhancing tumour which iswithin an anatomical body (e.g. human or animal body). The inventionrelates in particular to the determination of the presence or absenceand/or position and/or geometry (i.e. the size and/or shape) of thephysically-varying anatomical structure. The term “physically-varying”means in particular that the anatomical structure has undergone a changein its geometry and/or position and/or presence (existence) or absenceover time. In particular the anatomical structure expands or shrinksover time. Thus the physically-varying anatomical structure can be anexpanded or a shrinked anatomical structure. If in the following anexpanded anatomical structure is mentioned, this is meant as an examplefor the physically-varying anatomical structure. The term “physicallyvarying” means that the physically-varying anatomical structure hasvaried at least one of its physical properties (position, presence orabsence and/or geometry) at least during a time interval in the past butcan be invariable (non-changing physical properties) at the time ofgenerating images by an imaging method and/or currently. In other words,there can be time intervals when the physical properties vary and othertime intervals when the physical properties are static. If it ismentioned herein that the physically-varying anatomical structure is ina “different physical state”, then this means that at least one of thephysical properties of the physically-varying anatomical structure haschanged. The physically-varying anatomical structure can comprisedifferent elements, for instance growing elements, shrinking elements,necrotic elements, non-proliferative parts. The elements of thephysically-varying anatomical structure are in particular cells or cellcompounds (e.g. tumour cells). The delineation of the physically-varyinganatomical structure can be defined in different ways, for instance inthat the concentration of elements of the physically-varying anatomicalstructure within a healthy anatomical part is below a certainconcentration (described e.g. by a percentage of the number of tumourcells related to the total number of cells in a unit volume of theanatomical body) outside the delineation (e.g. a percentage limit of10%, 5% or 1%). Some of the elements of the physically-varyinganatomical structure can be contiguous to and others can be separatefrom other neighbouring elements of the physically-varying anatomicalstructure.

In the field of medicine, imaging methods are used to generate imagedata, for instance two-dimensional or three-dimensional image data, ofanatomical structures (such as soft tissues, bones, organs, pathologicalstructures like tumours, edema etc.) of the human body. Analyticaldevices are in particular used to generate the image data. The imagingmethods are in particular used for medical diagnostics, to analyse theanatomical body in order to generate images which are described by theimage data. The imaging methods are in particular used to detectpathological physical variations (i.e. change of physical properties) inthe human body. However, some of the physical variations in theanatomical structure, in particular the pathological physicalvariations, in particular physical variations of the pathologicalanatomical structure (called pathological structure) may not bedetectable and in particular may not be visible in the images generatedby the imaging methods. A growth of tumour for example represents anexample of a physical variation in both the healthy anatomical structure(in which the tumour is embedded) and in the pathological structure(i.e. the tumour). If the tumour had grown, the tumour then representsan physically-varying anatomical structure. If the tumour has respondedto treatment, then the tumour represents a shrinked anatomicalstructure. The physically-varying (in particular expanded or shrinked)anatomical structure may not be detectable by an analytical device; inparticular, it may be that only a part of the physically-varyinganatomical structure is detectable. Primary/high-grade brain tumours arefor example usually visible on MRI scans when using contrast agents toinfiltrate the tumour. The MRI scans represent an example of an imagingmethod. In the case of MRI scans of such brain tumours, the signalenhancement in the MRI images (due to the contrast agents infiltratingthe tumour) is considered to represent the solid tumour mass. Thus, thetumour is detectable and in particular discernible in the imagegenerated by the imaging method. In addition to these tumours, referredto as “enhancing” tumours, there are believed to be approximately 10% ofbrain tumours which are not discernible on a scan, the tumour itself isin particular not visible to a user looking at the image or imagesgenerated by the imaging method. In particular, the physically-varyinganatomical structure is not discernible e.g. to a user or anidentification algorithm. In other words, just a (suspicious) region ofthe image (which is filled by the changed anatomical structure, inparticular the tumour) do not include image information which allows todetermine (identify) the position and/or the presence and/or absenceand/or geometry of the changed anatomical structure in the (suspicious)region. In particular the delineation of the changed anatomicalstructure cannot be determined by a user or an algorithm, at least notdetermined in an accurate manner if the determination is only based onthe image content of the suspicious region.

Analytical devices of for instance x-ray devices, CT devices, MRIdevices, ultrasound devices or MRT devices are used to generateanalytical images (such as MRI images) of the body. Analytical devicesare in particular devices for analysing a patient's body, for instanceusing waves and/or radiation and/or energy beams, in particularelectromagnetic waves and/or radiation, ultrasound waves, particlebeams, etc. Analytical devices are in particular devices which generateimages (for instance, two-dimensional or three-dimensional images) ofthe patient's body (in particular of parts of the anatomical body, e.g.of anatomical structures) by analysing the body. Analytical devices arein particular used in medical diagnosis, in particular in radiology.

The following prior art documents relate to non-enhancing tumours:

-   a) “Automatic Segmentation of Non-enhancing Brain Tumors in Magnetic    Resonance Images”, Lynn M. Fletcher-Heath, Lawrence O. Hall,    Dmitry B. Goldgof and F. Reed Murtagh;-   b) US 2007/0133852 A1;-   c) US 2007/0280518 A1.-   d) “Simulated Brain Tumor Growth Dynamics Using a Three-Dimensional    Cellular Automaton”, A. R. Kansal, S. Torquato, G. R. Harsh, E. A.    Chiocca and T. S. Deisboeck-   e) “Temporal Lobe Perfusion Asymmetries in Schizophrenia”, James M.    Russell, Terrence S. Early, James C. Patterson, Justin L. Martin,    Javier Villanueva-Meyer and Molly D. McGee

The object of the present invention is to allow the provision of datadescribing a physically-varying anatomical structure, even if thephysically-varying anatomical structure is not discernible.

The above object is solved by the subject-matter of the independentclaims. The dependent claims are directed to advantageous embodiments ofthe invention.

In the following advantages, advantageous features, advantageousembodiments and advantageous aspects of the present invention aredisclosed. Different advantageous features can be combined in accordancewith the invention.

One feature of the physically-varying anatomical structure is that it ispresent in a region (referred to as the “varied region” or just in theway of an example as “expanded region”) of the anatomical body in whichit was not present before. Thus, other anatomical structures (other thanthe physically-varying anatomical structure) have been displaced by thephysically-varying anatomical structure. In particular, at least a partof the displaced anatomical part of the body which was within theexpanded region (in which the physically-varying anatomical structure ispresent) before the displacement is then situated outside the expandedregion (in which the physically-varying anatomical structure is present)after the displacement. Herein, a part of the body, i.e. an anatomicalpart of the anatomical body is shortly called “anatomical part”. Thepresent invention preferably uses this displacement to determine datacalled the physically-varying anatomical structure, in particular todetermine variation data which describe the physically-varyinganatomical structure, in particular the varied region. In particular,the present invention was image information on the displaced anatomicalpart.

In the following, the physically-varying anatomical structure is alsoreferred to as the “abnormal anatomical structure”, while the anatomicalpart of the body outside the physically-varying anatomical structure isreferred to as the “normal anatomical part”. The anatomical part of thebody which was present in the expanded region of the physically-varyinganatomical structure before the physically-varying anatomical structureemerged and started to expand is also referred to as the “normalanatomical part” and in particular the “displaced normal anatomicalpart”. In accordance with one embodiment of the invention, at least apart of the normal anatomical part, in particular the displaced normalanatomical part, can be detected using imaging methods. In accordancewith one aspect of the invention, the displacement of the displacednormal anatomical part is used to infer and in particular determine thephysically-varying anatomical structure, in particular in order todetermine the physically-varying anatomical structure and in particularthe expanded or shrinked region. An anatomical part, in particular anormal anatomical part can comprise one or more anatomical structures orone or more parts of anatomical structures.

The variation data in particular describe the presence or absence and/orposition and/or geometry of the physically-varying anatomical structure.The geometry of the physically-varying anatomical structure (and/or theexpanded region) is in particular the geometry (i.e. the size and/orshape) of the physically-varying anatomical structure itself, inparticular the geometry (i.e. the shape) of the surface of thephysically-varying anatomical structure, and/or in particular thegeometry (i.e. the size and/or shape) of the delineation (or boundary)of the physically-varying anatomical structure. Instead of or as well asdetermining the geometry of the physically-varying anatomical structure,the present invention is directed to determining the position of thephysically-varying anatomical structure, in particular the position ofthe surface of the anatomical structure, in particular the position ofthe delineation (boundary) of the anatomical structure. The presentinvention is also directed to determining variation data which describethe presence and/or position and/or geometry of the physically-varyinganatomical structure (and in particular the expanded region). Thevariation data in particular allow a determination as to whether a partof the anatomical body forms part of the physically-varying anatomicalstructure or not. In particular, the variation data describe whether aphysically-varying anatomical structure is present or not. The variationdata in particular describe the position or positions of at least a partof the physically-varying anatomical structure.

The present invention relates in particular to a data processing methodfor determining the variation data. This data processing method usesfirst image data which describe a first image and second image datawhich describe a second image. Preferably, the first and second imagedata are designed such that the displacement of the normal anatomicalstructure due to the expansion of the abnormal anatomical structure canbe determined. The variation data are preferably provided, in particulardetermined, on the basis of the determined displacement.

The method in accordance with the invention is in particular a dataprocessing method. The data processing method is preferably performedusing technical means, in particular a computer. The computer inparticular comprises a processor and a memory in order to process thedata, in particular electronically and/or optically. The calculatingsteps described are in particular performed by a computer. Determiningor calculating steps are in particular steps of determining data withinthe framework of the technical data processing method, in particularwithin the framework of a program. A computer is in particular any kindof data processing device. A computer can be a device which is generallythought of as such, such as for example desktop PCs or notebooks ornetbooks, etc., but can also be any programmable apparatus, such as forexample a mobile phone or an embedded processor. A computer can inparticular comprise a system (network) of “sub-computers”, wherein eachsub-computer represents a computer in its own right. A computer inparticular comprises interfaces in order to receive or output dataand/or perform an analogue-to-digital conversion. The data are inparticular data which represent physical properties and/or are generatedfrom technical signals. The technical signals are in particulargenerated by means of (technical) detection devices (such as for exampledevices for detecting marker devices) and/or (technical) analyticaldevices (such as for example devices for performing imaging methods),wherein the technical signals are in particular electrical or opticalsignals. The technical signals in particular represent the data receivedor outputted by the computer.

Where data are “provided”, this means that they are ready for use by themethod or program in accordance with the invention. The expression“providing data” encompasses (within the framework of a data processingmethod) in particular the scenario in which the data are determined bythe data processing method or program. The meaning of “providing data”in particular also encompasses the scenario in which the data arereceived by the data processing method or program (for example, fromanother program or a data storage), in particular for further processingby the data processing method or program. Thus, “providing data” canalso for example mean waiting to receive data and/or receiving the data.The received data can for instance be inputted via the interface.“Providing data” can also mean that the data processing method orprogram performs steps in order to (actively) acquire the data from adata source, for instance a data storage (such as for example a ROM,RAM, database, hard disc, etc.) or via the interface (for instance, fromanother computer or a network). The data can achieve the state of being“ready for use” by performing an additional step before the providingstep. In accordance with this additional step, the data are generated inorder to provide the data. The data are in particular detected orcaptured (for example, by an analytical device). Alternatively oradditionally, the data are inputted in accordance with the additionalstep, for instance via interfaces. The data generated can in particularbe inputted (for instance, into the computer). In accordance with theadditional step (which precedes the providing step), the data can alsobe provided by performing the additional step of storing the data in adata storage (such as for example a ROM, RAM, CD and/or hard drive),such that they are ready for use within the framework of the method orprogram in accordance with the invention. The providing step inparticular does not involve an invasive step which would represent asubstantial physical interference with the body requiring professionalmedical expertise to be carried out and entailing a substantial healthrisk even when carried out with the required professional care andexpertise. The providing step in particular does not involve a surgicalstep and in particular does not involve a step of treating a human oranimal body using surgery or therapy. This also applies in particular toany steps directed to determining data. Providing first data on thebasis of second data means in particular that the second data are usedby the method described herein to provide the first data. In order todistinguish the different data used by the method herein, the data aregiven names (i.e. called) like “XY data” and are defined by theinformation which they describe.

As mentioned above, one aspect of the present invention is a dataprocessing method for determining the variation data. The dataprocessing method preferably comprises the step of providing the firstimage data which describe the first image. The first image represents afirst anatomical part. The data processing method also preferablycomprises the step of providing the second image data which describe thesecond image. The second image is an image of a second anatomical part.The second anatomical part corresponds to the first anatomical part,wherein “corresponds” means in particular that the second image and thefirst image show the same region of an anatomical body. In the firstimage, however, the region does not include the physically-varyinganatomical structure or includes the physically-varying anatomicalstructure in a different physical state than in the second image. Thesecond image in particular shows the same region of an anatomical bodyas the first image, but the region shown by the second image includesthe physically-varying anatomical structure. In other words, the secondanatomical part includes the physically-varying anatomical structurewhich caused (resulted in) the aforementioned displacement of the normalanatomical structure, while the first anatomical part does not includethe physically-varying anatomical structure or includes thephysically-varying anatomical structure in a different physical statethan the second anatomical part. Thus, the first anatomical part doesnot include a displaced normal anatomical structure or includes a normalanatomical structure which has undergone a smaller displacement (atleast on average) than in the second anatomical part.

The second image data provided preferably describe a second image of aregion of the anatomical body, and the first image data providedpreferably represent a first image of the same region, i.e. if thephysically-varying anatomical structure were not present and allanatomical bodies were identical, the anatomical structure in this sameregion would be identical to the structure present in the regionrepresented by the second image. The first image can in particular befrom the same anatomical body as the second image or can be from adifferent anatomical body to the second image. (The second image can befor instance generated from a database which stores images of thedifferent anatomical body, in particular stores an atlas of thedifferent anatomical body. The different anatomical body can be a realanatomical body of a person or an average (typical) anatomical body asdescribed by an anatomical atlas) The first image can in particular befrom the same anatomical body, but at an earlier time than the secondimage, and represents the same region (referred to as the “anatomicalregion”). The anatomical region includes the “expanded region”. Thefirst image can also be determined, in particular calculated, from athird image of another region of the same anatomical body, wherein theanatomical part in this other region (referred to as the thirdanatomical part) has symmetry properties with respect to the anatomicalstructure in the aforementioned anatomical region (referred to above asthe “same region”) if the anatomical part is normal and healthy, i.e. ifthe physically-varying anatomical structure is not present in theanatomical region, wherein “symmetry properties” means in particularthat if an anatomical region is mirrored at a particular plane (forexample, the mid-sagittal plane) or point, this results in a mirroredanatomical region (the mirrored first anatomical part) which is at leastsimilar to said other region (the third anatomical part). Thus, thereare a number of ways of providing the first image data. Where it isstated here that the first and second images describe a region or imagesof a region, this means that the image comprises a representation ofthis region. Where it is stated here that an image is an image ofanother anatomical structure, this means that the image comprises arepresentation of said another anatomical structure, without excludingthe possibility that the image also comprises a representation of otheranatomical parts, in particular other anatomical structures. In a normalanatomical structure of a normal anatomical body, for example, theanatomical structure at least partly included in the first anatomicalpart and present in the first region is at least approximatelysymmetrical to the anatomical structure present in the second region,i.e. there is for example a symmetry property with respect to thesagittal plane, in particular the mid-sagittal plane. Thus, if the firstregion is for example mirrored at the mid-sagittal plane, this resultsin a mirrored first region comprising a (mirrored) anatomical structurewhich is at least similar to the anatomical structure of the secondregion, i.e. there is for example a symmetry property between the lefthemisphere and the right hemisphere of a brain. In accordance with oneembodiment, the symmetry property is used to calculate the first imagecomprising a representation of the first anatomical part, on the basisof a third image comprising a representation of a third anatomical partat the other symmetrical position (for example, the mirrored position)in particular with respect to the sagittal plane (in particular, themid-sagittal plane). Generating at least part of the first image datafrom the third image data in particular represents a transformationwhich involves determining a mirror image of the third anatomical partcomprised in the representation of the third image, wherein the plane(with respect to which the third anatomical part of the third image ismirrored) is in particular the sagittal plane. For instance theventricle structures in a brain exhibit symmetry properties which can beused to generate the first image data.

The image data described here are in particular generated using theabove-mentioned imaging methods, such as for instance MRI or CT, inparticular in order to generate two-dimensional and preferablythree-dimensional images. As mentioned above, the first image data canin particular be generated on the basis of a database comprising imagesof anatomical parts, in particular anatomical structures, in particularnormal anatomical structures, or can be generated on the basis of imagesof the third anatomical part (which exhibits the aforementioned symmetryproperties with respect to the first anatomical part shown by the firstimage).

Position change data are preferably provided on the basis of the firstand second image data. The position change data describe changes in theposition of corresponding image elements between the first image and thesecond image. The corresponding image elements in particular describethe elements of the anatomical part which undergo the aforementioneddisplacement due to the variation of physical properties of thephysically-varying anatomical structure. Thus, the corresponding imageelements are in particular outside the physically-varying anatomicalstructure. Thus, the present invention uses in particular image contentwhich describes part of the anatomical body which is outside thesuspicious region.

In accordance with one embodiment of the invention, some correspondingimage elements do not change their position due to variation of physicalproperties of the physically-varying anatomical structure but ratherremain at the same position and in particular do not change theirgeometry. These image elements are referred to as “non-changingcorresponding image elements” and can be used to register, in particularto scale and/or align (e.g. by translational and/or rotationaltransformation) the first and second images with respect to each other,such that there is at least a high degree of similarity in the positionsof the non-changing corresponding image elements and in particular acomplete overlap of the non-changing corresponding image elements. Afterthis registering, the changes in the position (referred to as the“positional changes”) of the corresponding image elements between thefirst and second images (i.e. from the first image to the second imageor from the second image to the first image) can be determined. A vectorcan for example be determined which connects the position of a firstimage element to the position of a second image element, wherein thefirst and second image elements correspond to each other and thusrepresent corresponding image elements and in particular a“correspondence pair”, as will be explained further below. Alternativelyor additionally, positional changes can be determined using atransformation from the first image to the second image, in particularby performing dynamic image fusion and in particular image morphing, aswill be explained further below. The position change data can beprovided automatically or semi-automatically. Providing the positionchange data semi-automatically in particular involves indicating (inparticular, displaying) the first and second images to the user,receiving data which describe the positions of corresponding imageelements and subsequently determining the position change data on thebasis of the corresponding image elements received. As mentioned above,the position change data can also be provided automatically, bydetermining the position change data on the basis of the first andsecond image data by transforming and/or scaling and/or aligning theimages. Automatically providing position change data in particularinvolves analysing the first and second image data in order to determinecorresponding image elements. This analysis in particular involvesdetermining similarities, in particular similarities between the imagesand/or similarities in the position and/or geometry of correspondingimage elements. Variation data are preferably provided on the basis ofthe position change data. This means in particular that the positionchange data are used by the data processing method to provide thevariation data. The variation data describe the physically-varyinganatomical structure, in particular the presence or absence and/orposition and/or geometry of the physically-varying anatomical structure,in particular the position and/or geometry of the delineation (boundary)of the physically-varying anatomical structure, in particular theposition and/or surface of the physically-varying anatomical structure.

The variation data can be provided semi-automatically, for instance byindicating the positional changes described by the position change data(to a user) for instance by outputting an indication using indicationsignals (audio, video, tactile), in particular an image via a userinterface, in particular graphical user interface GUI (which indication,in particular image represent the positional changes described by theposition change data) and then receiving the variation data by means ofa user input. Thus the variation data are provided on the basis of theposition change data. In particular, the semi-automatic provisionrepresents an example of using the position change data for providingthe variation data. The magnitude and/or direction of positional changescan in particular be indicated to the user in accordance with thepositions of “sub-regions” which are parts of the region shown by thefirst and second image. A sub-region can be an extended part of a regionor a point. A plurality of displayed vectors (originating at thepositions of different sub-regions) can indicate the magnitude and/ordirection of the positional changes of the sub-regions to a user. Thisenables a user to infer the position and/or geometry, in particular thesurface, in particular the delineation, of the physically-varyinganatomical structure, since the positional changes of the sub-regionsdue to the expansion are for example indicated to a user. The user caninput the result of this inference into the data processing method. Inother words, the data processing method receives the variation data fromthe user after indicating the position change data to the user. Inaccordance with another embodiment, the variation data are providedautomatically, in particular by being determined (automatically) fromthe position change data, as will be explained in more detail furtherbelow. Thus, the variation data are provided (i.e. automaticallydetermined) on the basis of the position change data. In particular, theautomatic determination represents an example of using the positionchange data for providing the variation data. The variation data are inparticular determined by analysing the positional changes, particularlyif the positional changes indicate a local expansion or compression involume.

In accordance with one embodiment of the data processing method, thestep of providing the position change data involves (automatically)determining a transformation in order to transform the first imageand/or the second image. The transformation is preferably described bydata called transformation data. If the transformation is applied to thefirst image, then the transformation results in a transformed image(referred to as the transformed first image). The transformation ispreferably such that the transformed first image is at least similar tothe second image, wherein “at least similar” means in particular thatthe transformed first image is more similar to the second image than the(untransformed) first image.

Within the context of this application, “at least similar” means inparticular that the degree of similarity is above a certain predefinedthreshold. The “measure of image similarity” quantifies the degree ofsimilarity between two images (in the given example, between the secondimage and the transformed first image). Examples of measures of imagesimilarity include for instance the sum of squared intensity differencesbetween the images, cross-correlation, mutual information and the ratioof image uniformity, and normalised mutual information. The thresholdcan be defined such that the degree of similarity is at least 70%, 80%,90%, 95% or 99%. In accordance with one embodiment, different candidatesfor the transformation are provided and applied to the first image. Themeasure of image similarity is then calculated for each candidate. Thecandidate transformation selected is the one which results in thetransformed first image exhibiting the greatest similarity (i.e. thehighest degree of similarity or greatest measure of image similarity) tothe second image. In accordance with another embodiment, the secondimage is transformed into a transformed second image which is preferablyat least similar to the first image. In this case, too, “at leastsimilar” has the corresponding meaning described above and thetransformation can in particular be determined by providing a pluralityof candidate transformations and selecting the one which results in thetransformed second image exhibiting the greatest similarity to the firstimage. The transformation preferably describes the positional changesbetween the first image and the transformed first image and/or betweenthe second image and the transformed second image. These positionalchanges are deemed to be the positional changes described by theposition change data and are in particular deemed to be the positionalchanges of corresponding image elements between the first and secondimages. In accordance with this embodiment, the position change datadescribe positional changes experienced by image elements when thedetermined transformation is applied. These positional changes aredeemed to represent the positional changes of corresponding imageelements between the first and second images. The transformation can inparticular be described using a vector field, The bases of the vectorsof the vector field preferably describe the positions of image elementsin the untransformed image, and the tips of the vectors describe thepositions of the corresponding image elements (in particular, the sameimage elements) in the transformed image.

The transformation is preferably determined on the basis of an imagemorphing algorithm. The image morphing algorithm is preferably appliedto the first image or the second image in order to transform one of thefirst and second images into the other of the first and second images.In this application, the term “image morphing” is also used as analternative to the term “image fusion”, but with the same meaning.

Image morphing transformations are in particular designed to enable aseamless transition from one image to another image. The transformationis in particular designed such that one of the first and second imagesis deformed, in particular in such a way that corresponding structures(in particular, corresponding image elements) are arranged at the sameposition as in the other of the first and second images. The deformed(transformed) image which is transformed from one of the first andsecond images is in particular as similar as possible to the other ofthe first and second images. Preferably, (numerical) optimisationalgorithms are applied in order to find the transformation which resultsin optimum similarity. As mentioned above, the degree of similarity ispreferably measured by way of a measure of similarity (also referred toin the following as a “similarity measure”), The parameters of theoptimisation algorithm are in particular vectors of a deformation fieldF. These vectors are determined by the optimisation algorithm whichresults in optimum similarity. Thus, optimum similarity represents acondition, in particular a constraint, for the optimisation algorithm.The bases of the vectors lie in particular at voxel positions of one ofthe first and second images which is to be transformed, and the tips ofthe vectors lie at the corresponding voxel positions in the transformedimage. A plurality of these vectors are preferably provided, forinstance more than twenty or a hundred or a thousand or ten thousand,etc. Preferably, there are (further) constraints on the transformation(deformation), in particular in order to avoid pathological deformations(for instance, all the voxels being shifted to the same position by thetransformation). The constraints include in particular the constraintthat the transformation is regular, which in particular means that aJacobian determinant calculated from a matrix of the deformation field(in particular, the vector field) is larger than zero. The constraintsinclude in particular the constraint that the transformed (deformed)image is not self-intersecting, in particular that the transformed(deformed) image does not comprise faults and/or raptures. Theconstraints include in particular the constraint that in case a regulargrid is transformed. Simultaneously with the image and in acorresponding manner, then the grid is not allowed to interfold at anyof its locations. The optimising problem is in particular solvediteratively, in particular by means of an optimisation algorithm whichis in particular a first-order optimisation algorithm, in particular agradient descent algorithm. Other examples for optimisation algorithmsare optimisation algorithms which do not use derivations like theDownhill Simplex algorithm or algorithms which use higher orderderivatives like Newton-like algorithms. Preferably, the optimisationalgorithm perform a local optimisation. In case of a plurality of localoptima, global algorithms like Simulated Annealing or Genetic Algorithmcan be used. In case of non-linear optimisation problems for instancethe Simplex method can be used.

In the steps of the optimisation algorithms, the voxels are inparticular shifted by a magnitude in a direction such that the degree ofsimilarity is increased. This magnitude is preferably less than apredefined limit, for instance less than 1/10 or 1/100 or 1/1000 of thediameter of the image, and in particular about equal to or less than thedistance between neighbouring voxels. Due in particular to a high numberof (iteration) steps, large deformations can be implemented.

As mentioned above, the position change data are preferably determinedby determining a similarity measure on the basis of the first and secondimage data. In particular, the similarity between the first and secondimage or between corresponding elements of the first and second imagesis determined. In particular, the similarity between one of atransformed first image and a transformed second image and the other ofthe first image and second image is determined. In particular, thesimilarity between image elements (for example, voxels) of thetransformed first or second image and image elements of the other of thefirst image and second image are determined.

In accordance with one embodiment, correspondence data are provided onthe basis of the first and second image data. The step of providingcorrespondence data can be a step of receiving the correspondence data,for example via a user interface, wherein a user for example inputs thecorrespondence data into the data processing method. The step ofproviding the correspondence data can also include the step ofindicating the first and second image data to the user. Providing thefirst and second image data thus comprises the steps of indicating thefirst and second image (on the basis of the first and second image data)and receiving the correspondence data. A user can for instance markcorrespondence pairs on a screen. The marked pairs are received by thedata processing method. The user can also for example mark typicallandmarks of a brain which correspond to each other and which areshifted due to the expansion of a tumour. The landmark is then marked inthe first image, and the corresponding (shifted) landmark is marked inthe second image. The two marked landmarks then represent an example ofa correspondence pair, which is inputted into the data processing methodwhich is being run on a computer.

In accordance with an alternative embodiment, the step of providing thecorrespondence pairs is performed automatically, i.e. an algorithmanalyses the first and second images for image elements which are atleast similar and for example represent landmarks of the anatomicalstructure which are shown by the first and second images. In this way, alandmark and a shifted landmark can be automatically identified in thefirst and second images. The correspondence pairs are thus automaticallyidentified.

The correspondence data comprise a description of correspondence pairs.The correspondence pairs are pairs of corresponding image elements ofthe first and second images. These pairs of corresponding image elementsare also referred to as “pairs of elements” or short. A correspondencepair, in particular each correspondence pair, includes and in particularconsists of a first element and a second element. The first element isin particular an image element of the first image, and the secondelement is in particular an image element of the second image. Inparticular, the first and second image elements correspond to eachother. This means in particular that they are at least similar to eachother, wherein “at least similar” has the meaning mentioned above, i.e.that the first and second images are for example more similar to eachother than to other image elements and/or that the first and secondimage elements exhibit a degree of similarity which is greater than acertain threshold and/or that neighbouring elements are also at leastsimilar to each other, as will be explained further below. Thecorrespondence data in particular describe the positions of the firstand second elements in the first and second images, respectively. Asmentioned above, a similarity measure is determined in accordance withone embodiment on the basis of the first and second image data. Theposition change data are preferably provided on the basis of thedetermined similarity measure. Determining the similarity measure on thebasis of the first and second image data can also be part of theembodiment described below. An image element can for instance compriseone or more voxels.

In accordance with one embodiment of the invention, the data processingmethod comprises the step of providing correspondence data on the basisof the first and second image data. The correspondence data comprise adescription of correspondence pairs (already mentioned above) which arepairs of elements of the first and second images. A first element (alsoreferred to as the “first image element”) of the correspondence pair isan image element of the first image. The second element (also referredto as the “second image element”) of the pair is an image element of thesecond image. The first and second elements are examples ofcorresponding image elements. Preferably, the first and second imageelement of a correspondence pair are at least similar to each other.

The positional change data are provided, in particular determined, onthe basis of the correspondence data. The positional change data aredetermined on the basis of the positions of the first and secondelements of a correspondence pair. The position change data are inparticular determined such that they represent a positional change whichcorresponds to a change in position from the position of one of thefirst and second elements of a correspondence pair to the position ofthe other of the first and second elements of the same correspondencepair. The change from a first position of the first element to a secondposition of the second element and/or from a second position of thesecond element to a first position of the first element is preferablydetermined for each of the correspondence pairs. The positional changeis for instance represented by a vector, and the plurality of positionalchanges can be represented by a vector field.

In accordance with one embodiment, position identity data are providedwhich describe the pairs which are assumed to represent correspondencepairs which have not undergone a change in position. Some body partswhich are for example distant from the physically-varying anatomicalstructure will not have been displaced, in particular deformed, by thephysically-varying anatomical structure. These body parts are preferablydescribed by image elements (the aforementioned non-changingcorresponding image elements), the position of which is preferablydescribed by the above-mentioned position identity data. These positionidentity data can be used to register, in particular to scale and/oralign the first and second images. The position change data arepreferably determined on the basis of the positions of the elements ofcorrespondence pairs after scaling has been performed if necessary. Itis also possible for the first and second images represented by thefirst and second image data to already be registered before they areprocessed by the data processing method in accordance with theinvention. In order to determine the position change data, the first andsecond images are for example registered with respect to each other,such that the identical image elements (the position of which isdescribed by the position identity data) overlap completely. Thedifference in position between a first and second element (described forexample by a vector) is then preferably determined and represents apositional change of a pair of corresponding image elements. If theimage elements are identical, then the positional change equals zero.However, a plurality of corresponding image elements, in particularcorrespondence pairs, preferably represent a positional change which isgreater than zero. The positional change can in particular be describedby a vector from one of the first and second elements to the other ofthe first and second elements of a correspondence pair.

As mentioned above, the correspondence data can be provided in a varietyof ways. They can for example be provided semi-automatically byoutputting indication data which represent the first and second images,in particular to a display, such that the first and second images areshown on the display. A user can then for example indicatecorrespondence pairs on the display, for example by marking thecorresponding elements on the displayed first and second images, whereinthe marked elements are then received as correspondence data. Thecorrespondence data in particular describe the position of the firstelement in the first image and the position of the second element in thesecond image of a correspondence pair designated (for example, marked)by a user.

In accordance with another embodiment which can be combined with theaforementioned embodiment, a plurality of image element datasets areprovided. The image element data can be provided by indicating the firstand second images, as mentioned above, when receiving a plurality ofimage elements which have for instance been designated by the user. Thedata processing method then determines whether the designated imageelements correspond to each other, as will be explained further below.In accordance with another embodiment, a plurality of image elements areautomatically determined, wherein elements of the image are for exampleselected which exhibit at least one of the following features: acontrast above a certain threshold value; an image energy level above acertain threshold value; a difference between the maximum grey level andminimum grey level in the image element which is above a certainthreshold value, etc. In accordance with another embodiment, the firstand second images are tessellated into a plurality of image elements.Preferably, the image elements provided are compared with each other inorder to determine a correspondence pair, wherein two of the pluralityof image elements provided are preferably determined such that theyrepresent the correspondence pair if at least one of the followingconditions is fulfilled:

-   -   a) in accordance with a first condition, the two image elements        (which are for instance compared with each other) are described        by received correspondence data which specify that the two image        elements represent a correspondence pair. A plurality of image        elements are for example shown to a user on a display. A grid is        for example superimposed over the first and second displayed        images, on the basis of the first and second image data. The        grid defines a plurality of image elements of the first and        second images. The user can then designate two of the image        elements which are believed to correspond to each other. The        correspondence data are generated on the basis of this        designation. The data processing method can then check whether        the received correspondence data, i.e. the received pair of        image elements, fulfil a condition of sufficient similarity (for        instance to the effect that the similarity measure has to be        above a certain threshold). The data processing method for        example accepts the received correspondence data as “provided        correspondence data” only if the condition is fulfilled.    -   b) In accordance with another embodiment, two image elements are        in particular automatically determined such that they represent        a correspondence pair if at least one of the following        conditions applies:        -   i) the image content of one of the two image elements (also            referred to in the following as the “first image element”)            is at least similar to the image content of the other of the            two image elements (also referred to in the following as the            “second image element”). The term “at least similar” has            already been described above. The image content is in            particular described by the one or more voxels (which the            image elements include) if the image is a three-dimensional            image or by the one or more pixels (which the image element            includes) if the image is a two-dimensional image.            Similarity measures are in particular used to determine the            similarity of the image content. In particular, the image            content represents the image represented by the image            element. In accordance with one embodiment, the geometry of            the first image element is in particular allowed to be            different from the geometry of the second image element. The            change in the geometry of an element of a body part due to            the deformation can thus be considered; and/or        -   ii) in accordance with another condition, the similarity of            neighbouring image elements which neighbour the first image            element is considered. In particular, the similarity between            neighbours of the first image element and neighbours of the            second image element is determined; in particular, it is            determined whether they are at least similar. If they are at            least similar, then the first and second image elements are            in particular considered to represent a correspondence pair.            The data processing method in particular uses correspondence            pairs which have already been determined in order to            determine whether the neighbourhood of two image elements            fulfils the similarity requirements. To this end, a first            neighbouring image element for example neighbours a first            image element and is also an element of a correspondence            pair which has already been determined. It is also assumed            that the second element of this correspondence pair likewise            neighbours the second image element. In accordance with one            embodiment, a similarity condition with respect to the            neighbourhood is fulfilled if the relative position between            the first neighbouring image element and the first image            element is at least similar to the relative position between            the second neighbouring image element and the second image            element. An at least similar relative position can be            defined as being fulfilled if for instance the distance does            not deviate by more than one percent, five percent or ten            percent and/or if the direction represented by a vector            connecting the first neighbouring image element to the first            image element and another vector connecting the second            neighbouring image element to the second image element is            within a predefined range. Preferably, the similarity            condition for the neighbourhood is deemed to be fulfilled if            the relative positions are similar for a plurality of first            and second neighbouring image elements, wherein the first            neighbouring image elements neighbour the first image            element and the second neighbouring image elements neighbour            the second image element. The similarity condition is in            particular deemed to be fulfilled if the plurality of first            and second neighbouring image elements which fulfil the            similarity condition exceed a certain number and/or if the            similarity condition is fulfilled for the majority of first            and second neighbouring image elements and/or if the            similarity condition is fulfilled for the relative positions            of more than a certain percentage of the first and second            neighbouring image elements (in particular, more than 60%,            70%, 80% or 90%).    -   c) In accordance with another embodiment, two image elements are        determined to be corresponding image elements of a        correspondence pair if one of the first and second image        elements is transformed into a third image element by a        transformation and the third image element has the same position        as the other of the two image elements. The transformation is a        transformation which transforms one of the first and second        images into the other of the first and second images. The        transformation in particular uses an image forming algorithm.        The transformation is thus used to determine whether an image        element of the first image corresponds to an image element of        the second image. The transformation is in particular a        transformation such as already been described above, i.e. a        transformation which transforms one of the first and second        images into a transformed image which is at least similar to the        other of the first and second images. The transformed image        comprises the third image element.

The data processing method preferably allows a delineation of thephysically-varying anatomical structure to be determined. To this end,the position change data preferably comprise data which describe thepositions at which the positional changes occur. These positions arereferred to here as “change positions”. The positional changes are forexample described by vectors. Each vector is preferably assigned aposition which describes the position of the vector. In accordance withone embodiment, a plurality of vectors are provided, in particular avector field. This field in particular describes the deformation of thefirst image into the second image and is therefore also referred to asthe deformation field (as already mentioned above). The deformationfield is a function of the positions (i.e. the change positions). Thedeformation field is referred to here in an abbreviated form as F(r),wherein the letter “r” represents the change position (in two or threedimensions) and can for instance be described by two (x, y) or threeco-ordinates (x, y, z). The function F is in particular a vector whichin particular describes the positional changes of pixels or voxels inaccordance with the change positions.

In accordance with this embodiment, compression-variation data arepreferably determined on the basis of the positional changes at thechange positions, in particular on the basis of F(r). Thecompression-variation data preferably describe where a transitionbetween a compression and an expansion occurs. In the case ofthree-dimensional images, the multiplicity (manifold) of positions atwhich the transition between the compression and the expansion occurs isin particular a surface, in particular a closed surface (a closedmultiplicity in two dimensions) which includes at least some andpreferably all of the physically-varying anatomical structure and whichin particular surrounds the physically-varying anatomical structure.This surface is also referred to here as the “variation surface”. Thedelineation of the physically-varying anatomical structure is inparticular determined on the basis of the variation surface; inparticular, the variation surface is deemed to correspond to thedelineation.

The variation surface can be determined in different ways. Additionalembodiments featuring alternative methods for determining the variationsurface will be described below.

In accordance with one embodiment, the delineation—in particular, theposition and/or geometry of the delineation—is determined on the basisof the determined variation surface. Preferably, a database is accessedwhich stores the relationship between the geometry of the variationsurface and the geometry of the delineation of the physically-varyinganatomical structure. The database in particular comprises relationshipdata which describe this relationship for different types ofphysically-varying anatomical structures (in particular, tumours) and/ordifferent types of anatomical body parts in which the physically-varyinganatomical structure is present. The relationship data can for exampledescribe that the physically-varying anatomical structure is greater orsmaller than the variation surface by a predefined factor (multiplier).This factor is in particular determined such that there is a highprobability that the physically-varying anatomical structure is withinthe delineation. The factor is an example of the relationship betweenthe aforementioned geometries of the variation surface andphysically-varying anatomical structure. The factor can depend on theaforementioned types, as described by the relationship data. This canreduce the risk of parts of the anatomical structure, in particularparts of the tumour, remaining in the body part after surgery.

In accordance with another embodiment, the variation surface isdetermined on the basis of the position at which the positional changeis at a maximum. In this respect, it is referred to A. R. Kansal et. al.J. theor. Biol. (2000), 203, 367-382 “Simulated Brain Tumor GrowthDynamics Using a Three-dimensional cellular Automation”.

The variation data preferably comprise a description of the positionand/or geometry of the variation surface and/or of the delineation.

In accordance with one embodiment, a region of the second image isdetermined to be a region in which expansion has occurred if voxelswithin the region are described (on the basis of the position changedata) as having changed their position towards the outer surface of thisregion. A region is also in particular described as being a region inwhich compression has occurred if the position change data indicate thatthe voxels inside the region have been displaced towards the centre ofthe region. In accordance with this embodiment, the variation surface isdetermined to be between regions in which an expansion has occurred andregions in which a compression has occurred.

In accordance with another embodiment, the positional changes arerepresented by a vector field, and the variation data are determined bycalculating a determinant of a Jacobian matrix of the vector field. Thisvector field is in particular the aforementioned deformation field F(r).The Jacobian determinant is preferably calculated for the plurality ofpositions r. The Jacobian determinant describes the change in volume atthe position r and is equal to one if there is no change in volume, butgreater than one if there is an expansion at the position r and lessthan one if there is a compression at the position r. In accordance withone embodiment, the Jacobian determinant is equal to one at a pluralityof positions, and these positions span the variation surface orrepresent the variation surface (if the plurality is a manifold). Thetransition between the compression and the expansion is in particulardescribed as occurring at positions which are between positions at whichthe Jacobian determinant is smaller than one and positions at which theJacobian determinant is greater than one. An expansion in volume is inparticular assumed to represent the growth of a tumour, and acompression in volume is in particular assumed to represent acompression of the normal anatomical structure. An expansion of thevolume which encompasses (but does not include) the physically-varyinganatomical structure can in particular present a shrinkage of the tumourand a compression of the volume (in which the physically-varyinganatomical structure is present) can also represent a shrinkage of thetumour.

As mentioned above, a variation surface which is determined on the basisof the Jacobian determinant can be used as a basis for determining thedelineation of the physically-varying anatomical structure, for instanceon the basis of a database as described above.

In accordance with another embodiment, the variation data are providedsemi-automatically. In accordance with this embodiment, the dataprocessing method outputs change indicating data and receives thevariation data. The change indicating data indicate the positionalchanges, in particular the magnitude and/or direction of the positionalchanges. The change indicating data are for example displayed on adisplay and for example describe a plurality of vectors which representthe positional changes. Alternatively or additionally, the changeindication data indicate the change in volume and in particular describethe degree of expansion and/or compression. The degree of positionalchange and/or the degree of compression and/or expansion can forinstance be colour-coded, and the corresponding parts in at least one ofthe first and second images can be coloured accordingly, wherein thecolour in particular represents the degree of change. A user viewing thedisplay can thus see which parts of the image have been compressed andwhich parts have expanded due to the growth of the physically-varyinganatomical structure. The data processing method preferably comprises aninputting step in order to receive the variation data which are inputtedby a user. The user can for instance mark the parts on an image whichare believed to represent the delineation of the physically-varyinganatomical structure, wherein the displayed indication data assist theuser during this marking process.

The present invention is also directed to a navigation system forcomputer-assisted surgery. This navigation system preferably comprisesthe aforementioned computer for processing the data provided inaccordance with the data processing method as described in any one ofthe preceding embodiments. The navigation system preferably comprises adetection device for detecting the position of the detection pointswhich represent the main points and auxiliary points, in order togenerate detection signals and to supply the detection signals generatedto the computer such that the computer can determine the absolute mainpoint data and absolute auxiliary point data on the basis of thedetection signals received. In this way, the absolute point data can beprovided to the computer. The navigation system also preferablycomprises a user interface for receiving the calculation results fromthe computer (for example the position of the main plane, the positionof the auxiliary plane and/or the position of the standard plane). Theuser interface provides the received data to the user as information.Examples of a user interface are a monitor or a loudspeaker. The userinterface can use any kind of indication signal (for example a visualsignal, an audio signal and/or a vibration signal).

The present invention is also directed to a method for navigating aninstrument, in particular using the above-mentioned navigation system.The method in particular comprises the steps, in particular all of thesteps, of one of the embodiments described above, in particular in orderto determine the variation data. In addition to the steps of theabove-mentioned embodiments of a data processing method, the method fornavigating an instrument also preferably comprises the step of providinginstrument position data which describe the position of an instrument. Amarker device is for example attached to an instrument, and the markersof the marker device are detected by the detection device of thenavigation system. The detection device in particular comprises one ormore cameras.

It is the function of a marker to be detected by a marker detectiondevice (for example, a camera or an ultrasound receiver), such that itsspatial position (i.e. its spatial location and/or alignment) can beascertained. The detection device is in particular part of a navigationsystem. The markers can be active markers. An active marker can forexample emit electromagnetic radiation and/or waves, wherein saidradiation can be in the infrared, visible and/or ultraviolet spectralrange. The marker can also however be passive, i.e. can for examplereflect electromagnetic radiation in the infrared, visible and/orultraviolet spectral range. To this end, the marker can be provided witha surface which has corresponding reflective properties. It is alsopossible for a marker to reflect and/or emit electromagnetic radiationand/or waves in the radio frequency range or at ultrasound wavelengths.A marker preferably has a spherical and/or spheroid shape and cantherefore be referred to as a marker sphere; markers can also, however,exhibit a cornered—for example, cubic—shape.

A marker device can for example be a reference star or a pointer or oneor more (individual) markers in a predetermined spatial relationship. Amarker device comprises one, two, three or more markers in apredetermined spatial relationship. This predetermined spatialrelationship is in particular known to a navigation system and forexample stored in a computer of the navigation system.

The method also preferably comprises the step of providing body partposition data. Body part position data describe the position of thesecond anatomical part. The body part position data can for instance begenerated using analytical devices which can in particular be used forimaging methods. Analytical devices such as x-ray devices, CT devices,MRI devices or MRT devices can be used to generate analytical images(such as x-ray images or MRT images) of the body. Analytical devices arein particular devices for analysing a patient's body, for instance usingwaves and/or radiation and/or energy beams, in particularelectromagnetic waves and/or radiation, ultrasound waves, particlesbeams, etc. Analytical devices are in particular devices which generateimages (for instance, two-dimensional or three-dimensional images) ofthe patient's body (in particular, internal structures and/or anatomicalparts) by analysing the body. Analytical devices are in particular usedin medical diagnosis, in particular in radiology.

In accordance with one embodiment, a marker device is attached to thebody in a fixed position relative to the second anatomical part. Theposition of the marker device relative to the second anatomical part isknown on the basis of the images, in particular three-dimensionalimages, of the second anatomical part which preferably also include animage of the marker device. The relative position between the instrumentand the second anatomical part can be determined, in particularcalculated, on the basis of detecting this marker device which isattached to the body and on the basis of the detected position of theinstrument.

In accordance with the method for navigating an instrument, the positionof the instrument relative to the physically-varying anatomicalstructure is preferably determined on the basis of the variation data,instrument position data and body part position data. In accordance witha preferred embodiment of the present invention, the variation datadescribe the position of the physically-varying anatomical structurerelative to the second anatomical part, in particular the position ofthe variation surface, in particular the position of the delineation (inparticular surface) of the physically-varying anatomical structurerelative to the second anatomical part, i.e. in particular in areference system in which the second anatomical part lies. The variationdata in particular describe the position (and geometry) of the expansionregion within the second anatomical part. In particular, the relativeposition between the second anatomical part and the instrument iscalculated on the basis of the instrument position data and the bodypart position data. The relative position between the instrument and thephysically-varying anatomical structure, in particular the variationsurface, in particular the delineation of the physically-varyinganatomical structure, is then calculated on the basis of the variationdata which describe the relative position between the physically-varyinganatomical structure and the second anatomical part, wherein “geometry”means size and/or shape.

The present invention is also directed to a program which, when runningon a computer or when loaded onto a computer, causes the computer toperform the steps of at least one of the above-mentioned embodiments ofthe data processing method. The present invention is also directed to aprogram storage medium, in particular a non-transitory program storagemedium on which the program is stored. The present invention is alsodirected to a computer on which the program is running or into thememory of which the program is loaded, in particular in a non-transitoryform. The present invention is also directed to a signal wave, inparticular a digital signal wave, carrying information which representsthe program. The program in particular comprises code means which areadapted to perform the steps of at least one of the embodiments of thedata processing method described herein and in particular all of thesteps of the respective embodiments.

As mentioned above, the present invention is in particular directed to anavigation system which is in particular used in computer-assistedsurgery. The navigation system preferably comprises the aforementionedcomputer for determining the variation data and a detection device fordetecting the position of the instrument and the position of the secondanatomical part. The detection device is preferably designed to transmitthe detection signals to the computer. The computer is preferablydesigned to receive the detection signals and in particular to transformthe detection signals into the detection data, The detection data inparticular comprise the above-mentioned instrument position data. Thecomputer is also preferably designed to receive body part position datawhich can be generated by the above-mentioned analytical devices whichgenerate an image of the second anatomical part by means of theabove-mentioned imaging method. The body part position data arecalculated on the basis of the known spatial relationship between thereference system of the navigation system and the region displayed bythe images generated by the analytical device. Additionally oralternatively, the detection device can be used to detect a markerdevice which is attached to the anatomical body, in order to generatethe body part position data. The relative positions between the markerdevice which is attached to the anatomical body and the secondanatomical part are preferably determined by analysing the imagesgenerated by the analytical devices. The analytical devices preferablydetect both the structure of the second anatomical part and the markerdevice which is attached to the anatomical body. The relative positionbetween the marker device which is attached to the body and the secondanatomical part is determined on the basis of these images. Thedetection device also preferably detects the position of the markerdevice which is attached to the anatomical body. The analytical devicepreferably transmits a signal, which represents the image generated fromthe anatomical body and the marker device, to the computer. Thedetection device also preferably transmits signals, which represent theposition of the marker device which is attached to the anatomical body,to the computer, The computer preferably determines the body partposition data, which describe the position of the second anatomical bodyin a reference system of the navigation system, in particular relativeto the position of the instrument, on the basis of these two signals.

Within the framework of the invention, computer program elements can beembodied by hardware and/or software (this also includes firmware,resident software, micro-code, etc.). Within the framework of theinvention, computer program elements can take the form of a computerprogram product which can be embodied by a computer-usable orcomputer-readable storage medium comprising computer-usable orcomputer-readable program instructions, “code” or a “computer program”embodied in said medium for use on or in connection with theinstruction-executing system. Such a system can be a computer; acomputer can be a data processing device comprising means for executingthe computer program elements and/or the program in accordance with theinvention. Within the framework of this invention, a computer-usable orcomputer-readable medium can be any medium which can include, store,communicate, propagate or transport the program for use on or inconnection with the instruction-executing system, apparatus or device.The computer-usable or computer-readable medium can for example be, butis not limited to, an electronic, magnetic, optical, electromagnetic,infrared or semiconductor system, apparatus or device or a medium ofpropagation such as for example the Internet. The computer-usable orcomputer-readable medium could even for example be paper or anothersuitable medium onto which the program is printed, since the programcould be electronically captured, for example by optically scanning thepaper or other suitable medium, and then compiled, interpreted orotherwise processed in a suitable manner. The computer program productand any software and/or hardware described here form the various meansfor performing the functions of the invention in the exampleembodiments. The computer and/or data processing device can inparticular include a guidance information device which includes meansfor outputting guidance information. The guidance information can beoutputted, for example to a user, visually by a visual indicating means(for example, a monitor and/or a lamp) and/or acoustically by anacoustic indicating means (for example, a loudspeaker and/or a digitalspeech output device) and/or tactilely by a tactile indicating means(for example, a vibrating element or vibration element incorporated intoan instrument).

The analytical device is in particular designed such that it cannotdetect the delineation of the physically-varying anatomical structureand/or the physically-varying anatomical structure itself and/or aportion of the physically-varying anatomical structure, but can inparticular detect at least some (in particular, most) of the remainderof the second anatomical part which does not form part of thephysically-varying anatomical structure. The analytical device is inparticular designed to detect the delineation of the remainder, inparticular the delineation which is adjacent to the physically-varyinganatomical structure and/or encloses the physically-varying anatomicalstructure. The body part position data in particular describe theposition and/or geometry (i.e. the size and/or shape) of the secondanatomical part, in particular within the reference system of thenavigation system.

The navigation system also preferably comprises an indication device forvisually and/or acoustically and/or tactilely indicating the determinedrelative position (between the instrument and the physically-varyinganatomical structure). The indication device receives said data from thecomputer. The indication device can be a display, loudspeaker, vibrationelement, etc. The indication device is designed to generate indicationsignals (for instance, images or sounds) on the basis of the receiveddata, in order to indicate the relative position between the instrumentand the physically-varying anatomical structure. The computer inparticular comprises an interface which converts data into signals, suchas for instance electrical signals or optical signals. The interface inparticular converts indication data into indication signals forindicating: the position change data; the magnitude and/or direction ofpositional changes of corresponding elements, in particularcorrespondence pairs; the expanded structure, in particular the positionand/or geometry of the expanded structure; a delineation of the expandedstructure, the variation surface and/or the relative position betweenthe instrument and the expanded structure. The signals are in particulartechnical signals.

The following detailed description of the invention discloses additionalembodiments, in particular features, of the invention. Differentfeatures of different embodiments can be combined.

FIG. 1 shows the steps of a method in accordance with the invention.

FIG. 2 shows the compression and expansion of a vector field.

FIG. 3 shows a navigation system in accordance with an embodiment of theinvention.

The following detailed description refers just as an example to the casewhere the variation of physical property is an expansion. Thus, thephysically-varying anatomical structure is an “expanded structure”.

FIG. 1 shows five steps which form part of a method in accordance withan embodiment of the invention and bear the reference signs S10, S20,S30, S40 and S50, respectively. A small illustration appears immediatelyto the left of each of the reference signs “S10” to “S50”, and these arereferred to as “sub-figures”. These sub-figures are thus referred to assub-figures “S10” to “S50”, respectively.

Step S10 relates to acquiring baseline imaging data. These baselineimaging data represent the aforementioned first image data. The baselineimage data show an anatomical structure which does not include aphysically-varying anatomical structure. As mentioned above, thebaseline image data (first image data) can be acquired by means ofanalytical devices. Thus, the result of step S10 is that the first imagedata are provided. Sub-figure S10, between the method step description“acquire baseline image data” and the reference sign “S10”, represents agrid of image elements of the first image, some of which bear referencesigns (10, 12, 14, 16, 18, 20, 22 and 24). These image elements are inparticular distinguishable image elements which in particular exhibit anidentifiable structure. The image elements represent elements of thefirst anatomical part.

Step S20 relates to providing the second image data. The second imagedata are provided by acquiring data with suspected volumetric changes.The image elements 10′ to 24′ (in sub-figure S20) represent elements ofthe second anatomical part which includes the indiscernible (invisible)physically-varying anatomical structure. The physically-varyinganatomical structure causes the image elements 10 to 24 to be displacedto the positions of the image elements 10′ to 24′. Thus, the imageelements 10 to 24 of S10 are shown as the displaced image elements 10′to 24′ in sub-figure S20 between the method step description “acquiredata with suspected volumetric changes” and the reference sign “S20” inFIG. 1. The image elements of sub-figure S20 (which correspond to theimage elements of sub-figure S10) are accordingly marked with the samereference number as the image elements of sub-figure S10, but with aprime, such that the image element 10 in sub-figure S10 corresponds tothe image element 10′ in sub-figure S20, the image element 12 insub-figure S10 corresponds to the image element 12′ in sub-figure S20,etc. By comparing the sub-figure shown in S10 with the sub-figure shownin S20, it can be seen that the image elements 10′ to 24′ in sub-figureS20 have been displaced as compared to the image elements 10 to 24 insub-figure S10, such that there is a void in the middle of the imageelements of sub-figure S20 which may be due to an expanded structurewhich is not discernible, i.e. the expanded structure is in particularnot shown in sub-figure S20 which is in particular generated using ananalytical device. Sub-figure S10 corresponds to the first imagedescribed by the first image data, and sub-figure S20 corresponds to thesecond image described by the second image data.

Both sub-figure S10 (which is a simplified example of a first image) andsub-figure S20 (which is a simplified example of a second image) arepreferably used in step S30. Steps S30 and S40 are preferably used toprovide the position change data.

In step S30, a transformation is preferably determined which, if appliedto the first image (sub-figure S10), transforms the first image into thesecond image (sub-figure S20). The transformation results in particularfrom dynamic image fusion, in particular from an image morphing processwhich morphs the first image into the second image. The transformationdetermined in step S30 in particular represents the positional changes(10 v to 24 v shown in sub-figure S30) of the corresponding imageelements. The transformation can be represented by a vector field F(r)(see sub-figure S40), wherein the vectors 10 v, 12 v, 14 v, 16 v, 18 v,20 v, 22 v and 24 v of the vector field in particular represent thepositional changes of the corresponding image elements from the positionof the image elements 10, 12, 14, 16, 18, 20, 22 and 24 to the positionof the image elements 10′, 12′, 14′, 16′, 18′, 20′, 22′ and 24′. Thevectors in particular describe the dislocation of voxels of the firstimage which results in an image which is at least similar to the secondimage and preferably identical to the second image.

Step S50 relates to providing the variation data. In step S50, thevariation data are determined on the basis of the vector fielddetermined in step S40. The variation data in particular describe theposition and geometry of the physically-varying anatomical structure 100which is shown in sub-figure S50 (between the method step description“calculate and display object in 2D and 3D” and the reference sign“S50”). As mentioned above, the surface of the expanded structure (the“variation surface”) can in particular be calculated on the basis of adeterminant of the Jacobian matrix of the vector field determined instep S40. The surface of the expanded structure 100 is in particulardetermined by setting the Jacobian determinant to 1. The vectors of thevector field are a function of the position within the second image. Thevariation surface is in particular defined by the positions at which thedeterminant of the Jacobian matrix equals 1.

FIG. 2 shows a transition between an expanding field of vectors and acompressing field of vectors. The border of the region within which thevectors describe an expansion, in particular an expansion in volume, isused to define the delineation. As shown in the embodiment of FIG. 2,the delineation 110 of the expanded structure 100 is defined such thatit is equal to the border of the expansion region, in particular equalto the transition between the fields of expansion and compression. Thetransition is shown by the arrow 120 in FIG. 2. The transition 120occurs between the delineation 110 of the expanded structure 100 and thedelineation 210 of the compressed structure 200. As can be seen in FIG.2, the length of the vectors are at a maximum at the delineation 110 ofthe expanded structure. In accordance with one embodiment, thedelineation of the expanded structure is therefore defined on the basisof the positions at which the vector length is at a maximum.

FIG. 3 shows a navigation system in accordance with an embodiment of theinvention. A patient's body 150 comprises an anatomical structure 160,such as for example the brain. An physically-varying anatomicalstructure 100, for instance a tumour, is situated within the anatomicalstructure 160. The tumour 100 has compressed the healthy brain tissuearound the tumour 100, hence there has been expansion within the regionof the expanded structure 100 and compression within the region outsidethe structure 100. The above-mentioned first image, which does not showthe physically-varying anatomical structure or only shows thephysically-varying anatomical structure in a different physical state,has for example been generated before the growth of the tumour. In orderto generate the first image, a so-called C-arc (also referred to as aC-arm) 300 is an example for the above-mentioned analytical devices(like MR devices, CT devices etc.) and is for example used to generate atwo-dimensional and/or a three-dimensional image of the secondanatomical part (for example, the brain). The C-arc is in particularconstituted to generate three-dimensional images similar to those knownfrom a CT. The same analytical device (i.e. for example the C-arc or MRdevice) 300 can subsequently be used to generate the second image whichis a two-dimensional or three-dimensional image. The C-arc isschematically shown in FIG. 3 and bears the reference sign 300. TheC-arc 300 for example comprises a fluoroscope 320 which is shown at thetop of the arc in FIG. 3. The fluoroscope 320 preferably generates animage of both the second anatomical part (for example, the brain) andthe marker device 400 which comprises the markers 401, 402 and 403. Themarker device 400 is for instance attached to a bone structure such asfor example the skull. The image data generated by the analytical device(i.e. for example the C-arc or the CT device) are transferred via a line310 to the computer 500. The computer 500 preferably generates thethree-dimensional image, in particular the first and/or second image.The second image preferably represents the marker device 400 and thesecond anatomical part including the physically-varying anatomicalstructure. The delineation of the physically-varying anatomicalstructure 100 is in particular not discernible in the second image. Inorder to determine the delineation of the physically-varying anatomicalstructure 100, the computer 500 preferably has a program loaded onto itwhich performs the data processing method described above. The programis in particular run on the computer 500. The program calculates theposition of the delineation of the physically-varying anatomicalstructure 100 on the basis of the first and second images, as describedfurther above. The relative position between the delineation of thephysically-varying anatomical structure 100 and the marker device 400 ispreferably determined, in particular calculated, by the computer 500.The computer 500 also receives data from a detection device 600 which isin particular a camera, in particular a stereoscopic camera. Thedetection device 600 transmits detection signals, received from themarker device 400, to the computer 500. The detection device 600 alsoreceives detection signals from the instrument 700 which has two markers701 and 702 attached to it which act as a marker device 705. Therelative position between the marker device 705 (comprising the markers701 and 702) and the instrument 700, in particular the tip of theinstrument 700, is preferably stored in a database to which the computer500 has access. The detection signals of the detection device 600, whichrepresent the position of the marker devices 400 and 705, are thuspreferably transmitted to the computer 500 via the line 610. Thecomputer 500 preferably calculates the relative position between themarker device 705 and the marker device 400 on the basis of thesedetection signals. Since the relative position between the marker device400 and the delineation of the physically-varying anatomical structure100 has been calculated on the basis of the data processing methodaccording to the present invention, the computer 500 can and preferablydoes then calculate the relative position between the marker device 705and the delineation of the physically-varying anatomical structure 100.The computer 500 in particular determines the relative position betweenthe tip of the instrument 700 (using the known relative position betweenthe marker device 705 and the tip of the instrument 700) and thephysically-varying anatomical structure 100, in particular thedelineation of the physically-varying anatomical structure 100. Thedetermined relative position between the instrument 700, in particularthe tip of the instrument 700, and the physically-varying anatomicalstructure 100, in particular the delineation of the physically-varyinganatomical structure 100, is shown on the display 510 of the computer500. A mouse 512 and a keyboard 514 are attached to the computer 500 forinputting purposes.

The image displayed on the display 510 in particular shows the firstand/or second anatomical part, in particular for example the brain or apart of it, and in particular the physically-varying anatomicalstructure 100 and a representation of the instrument 700, in particularin two or three dimensions.

1. A data processing method for providing variation data which describea non-enhancing tumor, comprising the steps of: providing second imagedata which describe a second image of a region of an anatomical body,wherein the region includes a second anatomical part which includes thenon-enhancing tumor; providing first image data which represent a firstimage of the same region, wherein said same region includes a firstanatomical part which does not include non-enhancing tumor or whichincludes non-enhancing tumor in a different physical state than in thesecond anatomical part; providing position change data which describepositional changes of corresponding image elements between the firstimage and the second image, on the basis of the first and second imagedata; and a) wherein the description of the positional changes providedby the position change data comprises change positions which define thepositions at which the positional changes occur, and the methodcomprises the steps of: determining the position at which the change inposition is at a maximum; determining the variation data, in particulara delineation of the non-enhancing tumor, on the basis of the positionsat which the change is at a maximum, wherein the variation data comprisea description of a position and geometry of a delineation of thenon-enhancing tumor; or b) wherein: the positional changes arerepresented by a vector field; and the step of determining the variationdata involves calculating a determinant of a Jacobian matrix of thevector field and of determining a position and geometry of a surface ofthe non-enhancing tumor by setting the determinant equal to
 1. 2. Thedata processing method according to claim 1 wherein: a) the first andsecond images describe the same region of the same anatomical body, butthe first image was generated at an earlier point in time than thesecond image, wherein the non-enhancing tumor did not exist at saidearlier point of time or was in a different physical state than at thelater point in time at which the second image was generated; or b) thefirst and second images describe the same region of a first and secondanatomical body, respectively, wherein the first anatomical body isdifferent to the second anatomical body and the first anatomical part ofthe first anatomical body does not include the non-enhancing tumor oronly includes the non-enhancing tumor in a different physical state thanin the second anatomical part; or c) the first image data have beengenerated on the basis of third image data which describe a third imageof another region which includes a third anatomical part, wherein thefirst and third anatomical parts are from the same anatomical body andthe third anatomical part has a symmetry property such that a structureof the third anatomical part would be at least approximately symmetricalto the second anatomical part if the non-enhancing tumor had not grownin the region which includes the second anatomical part, wherein thefirst image data are generated from the third image data by transformingthe third image data into the first image data in consideration of thesymmetry property.
 3. The data processing method according to claim 1,wherein the step of providing the position change data involvesdetermining transformation data describing a transformation for one ofthe first and second images which, if applied to one of the first andsecond images, results in a transformed image which is at least similarto the other of the first and second images, and providing the positionchange data on the basis of the determined transformation data.
 4. Thedata processing method according to claim 3 wherein the transformationdata are determined using an image morphing algorithm.
 5. The dataprocessing method according to claim 1, comprising the steps of:providing correspondence data on the basis of the first and second imagedata, wherein the correspondence data comprise a description ofcorrespondence pairs which are pairs of corresponding image elements ofthe first and second images, wherein a first element of thecorrespondence pair is an image element of the first image, and a secondelement of the correspondence pair is an image element of the secondimage, and wherein the first and second elements of a correspondencepair correspond to each other; providing the position change data on thebasis of the correspondence data; wherein the position change data forat least some of the correspondence pairs describe a positional changein the corresponding image elements as a change from a position of oneof the first and second elements of one of the correspondence pairs to aposition of the other of the first and second elements of the samecorrespondence pair.
 6. The data processing method according to claim 1,wherein the first and second images are registered with respect to eachother on the basis of corresponding image elements which have notchanged their position, and the position change data are provided on thebasis of the registered images.
 7. The data processing method accordingto claim 1, wherein the step of providing correspondence data involves:determining image indication data on the basis of the first and secondimage data, wherein the image indication data indicate the first andsecond image; and receiving the correspondence data; and/or wherein thestep of providing correspondence data involves: providing image elementdata which describe a plurality of image elements; determining two ofthe provided plurality of image elements to be corresponding imageelements of a correspondence pair if the two image elements aredescribed as corresponding to each other by received correspondenceindication data and/or if at least one of the following conditionsapplies: the image content of the first of the two image elements is atleast similar to the image content of the second of the two imageelements; and a first neighbouring image element neighbours the firstimage element and forms a correspondence pair with a second neighbouringimage element which neighbours the second image element, wherein therelative position between the first neighbouring image element and thefirst image element is at least similar to the relative position betweenthe second neighbouring image element and the second image element, andthis similarity in the relative positions is given for a plurality offirst and second neighbouring image elements; and/or if they aretransformed into each other by a transformation which transforms one ofthe first and second images into the other of the first and secondimages.
 8. The data processing method according to claim 1, wherein themethod comprises the steps of: determining compression-variation data,which describe where a transition between a compression and an expansionoccurs, on the basis of the positional changes and the change positions;and determining the variation data by determining a delineation of thenon-enhancing tumor on the basis of the compression-variation data. 9.(canceled)
 10. (canceled)
 11. The data processing method according toclaim 1, wherein the step of providing the variation data comprises thesteps of: determining change indication data on the basis of theposition change data, wherein the change indication data indicate thechanges in volume between the first and second images and/or theirpositional changes; and receiving the variation data.
 12. A method fornavigating an instrument, comprising the steps of: performing the stepsof the method of claim 1 in order to determine the variation data;providing instrument position data which describe the position of aninstrument; providing body part position data which describe theposition of the second anatomical part; and determining the relativeposition of the instrument relative to the non-enhancing tumor on thebasis of the variation data, the instrument position data and the bodypart position data, in order to navigate the instrument.
 13. A programwhich, when running on a computer or when loaded onto a computer, causesthe computer to perform the method according to claim 1 and/or a programstorage medium on which the program is stored and/or a computer on whichthe program is running or into the memory of which the program is loadedand/or a signal wave, in particular a digital signal wave, carryinginformation which represents the program, wherein the aforementionedprogram in particular comprises code which is adapted to perform all thesteps of the method according to any one of the preceding claims.
 14. Anavigation system for computer-assisted surgery, comprising: a computerloaded with the program of claim 13 or on which the program of claim 13is running, for determining the variation data and for receiving bodypart position data which describe the position of the second anatomicalpart; a detection device for detecting the position of an instrument andthe position of the anatomical body and for transmitting detectionsignals to the computer, wherein the computer is designed to determinethe relative position between the instrument and the non-enhancing tumoron the basis of the detection signals and the variation data; anindication device for receiving data, which describe the determinedrelative position, from the computer and for indicating the relativeposition between the instrument and the non-enhancing tumor on the basisof the received data.
 15. A method comprising the method according toclaim 1, wherein: an analysis of a body is performed by means of ananalytical device for generating the second image data; and/or theposition of the instrument and/or the second anatomical part is detectedby means of a detection device; and/or an indication signal is outputtedby means of an interface, in order to indicate at least one of thefollowing: the position change data; the magnitude and/or direction ofpositional changes of correspondence pairs; the position and/or geometryof the non-enhancing tumor; a position and/or geometry of a delineationof the non-enhancing tumor; and the relative position between theinstrument and the non-enhancing tumor; wherein the interface convertsdata outputted by the computer into the indication signal.